Efficacy of balance training on postural control in patients with rotator cuff disease: a randomized controlled study
Bibliographic record
Abstract
We evaluated the efficacy of adding balance training to a physical therapy program on postural control and health-related quality of life in patients with rotator cuff disease. Forty-two participants were randomly allocated to the control and intervention groups. Both groups received physical therapy (education, stretching, supervised strength training, and home exercise program) 3 days/week for 6 weeks. The intervention group was instructed to perform balance exercises at home. The primary outcomes were the stability index, the Fourier transformation (F5 and F6), the weight distribution index, and the fall index, as assessed by the posturography during eight conditions with different combinations of standing (solid surface, pillows, and different head positions) and vision (eyes open/closed). The secondary outcomes included the Western Ontario Rotator Cuff Index to assess the health-related quality of life, the Shoulder Pain and Disability Index, and the Numeric Pain Rating Scale. The adherence to in-person and home-based therapy was high (>83%). The intervention group significantly improved the stability index, F5, and F6 parameters but each in only one condition (P < 0.05). No significant improvement was found in the conditions for the other primary outcomes and in the health-related quality of life. (P > 0.05). We conclude that adding the balance training protocol to the physical therapy program does not improve postural control and health-related quality of life in patients with rotator cuff disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".